Introducing Target-to-Evidence by Stratzie Mirai: Turning AI Governance from Policy into Practice

A practical, evidence‑led approach for identifying AI use, assigning responsibility, establishing appropriate controls, and demonstrating that governance is working. In this post, we take a closer look at Target-to-Evidence  — Stratzie Mirai's AI governance solution and practical implementation framework.

Many organisations now have AI principles, policies, committees and risk frameworks. Yet senior management still struggles to answer operational questions:

What AI is actually being used? Who owns it? What can it do? What does it depend on? Is anyone monitoring changes? Are people behaving differently because the controls exist? Can we demonstrate that governance is working?

AI Governance Solution & Implementation Framework

Target-to-Evidence by Stratzie Mirai turns AI governance requirements into clear responsibilities, practical controls, organisational capabilities, observable behaviours and measurable outcomes. It is a web-based AI governance solution and implementation framework that connects governance intent to everyday action through the five-stages:

1. T - Target

   Governance begins by identifying a single, concrete concern and defining the outcomes the organisation wants to achieve. This prevents the work from drifting into an open‑ended review with no clear measure of success..

2. R - Reveal

   Map how work is performed today. Through stakeholder interviews, document reviews, and operational evidence, identify where AI is being missed, where ownership gaps exist, and where processes break down.

3. A - Architect

   Create practical, proportionate governance checks and assign clear ownership. Build controls that support real workflows rather than introduce unnecessary bureaucracy.

4. C - Change

   A control on paper falls short. People need to know when a control is relevant, understand the actions expected, and have the confidence and support to follow through. It maps the capabilities and behaviours required to embed governance into daily practice.

5. E - Evidence

   Define the evidence that will confirm each check was performed and whether it is delivering the intended result. Evidence chains and governance indicators give leaders a clear view of what is working and where intervention is required.

Organisations rarely need to tackle AI governance in its entirety. Progress often begins with one well‑chosen issue. Target-to-Evidence  delivers a tightly scoped 2–3 week proof‑of‑concept that applies all five stages to a single priority area, such as AI visibility, within one business function and a defined set of tools or workflows. It operates at three levels : Focus, Visibility & Core. Organisations can select the level(s) that best match the governance challenge to be addressed.

This governance solution produces eight integrated outputs—from the Target Statement, Diagnostic, Gap‑to‑Control Map, and Governance Logic Map through to the Ownership Map, Behaviour & Capability Map, Evidence Chains, and Governance Indicators—consolidated into a concise findings pack with practical tools for immediate use. It also delivers a 90‑Day Governance Activation Plan that summarises engagement performance and provides a prioritised roadmap showing next steps, ownership for each action, the evidence to retain, and how progress will be reviewed.

Target‑to‑Evidence by Stratzie Mirai is designed to complement an organisation’s existing policies, risk systems, and professional advice. It does not replace human judgment. Instead, it gives leaders and practitioners a structured way to move from concern to action, and from action to evidence. This practical emphasis aligns with leading international guidance, such as the NIST AI Risk Management Framework, which treats governance as a continuous activity.

In conclusion, the central idea behind Target-to-Evidence by Stratzie Mirai is simple: good AI governance should not end with a policy. It should be visible in decisions, ownership, behaviour, and evidence.

Interested in applying Target‑to‑Evidence to one priority AI governance issue in your organisation? Drop us a line to discuss the next steps for your team.